



'''simple docstring'''






def  lowerCamelCase__			(		_A					,     _A							):

  def get_matched_characters(_A					,     _A							) -> str:
    a		:   Optional[int]	  =	[]
    a		:   Dict	  =	min(len(_stra							)					,     len(_stra							)							) // 2
    for i, l in enumerate(_stra							):
      a		:   Any	  =	int(max(0					,     i - limit							)							)
      a		:   int	  =	int(min(i + limit + 1					,     len(_stra							)							)							)
      if l in _stra[left:right]:
        matched.append(_A							)
        a		:   Optional[Any]	  =	f"""{_stra[0:_stra.index(_A							)]} {_stra[_stra.index(_A							) + 1:]}"""

    return "".join(_A							)

  # matching characters
  a		:   Any	  =	get_matched_characters(_A					,     _A							)
  a		:   int	  =	get_matched_characters(_A					,     _A							)
  a		:   List[Any]	  =	len(_A							)

  # transposition
  a		:   Optional[Any]	  =	(
      len([(ca, ca) for ca, ca in zip(_A					,     _A							) if ca != ca]							) // 2
  )

  if not match_count:
    a		:   Dict	  =	0.0
  else:
    a		:   Optional[int]	  =	(
        1
        / 3
        * (
            match_count / len(_A							)
            + match_count / len(_A							)
            + (match_count - transpositions) / match_count
        )
    )

  # common prefix up to 4 characters
  a		:   Tuple	  =	0
  for ca, ca in zip(stra[:4]					,     stra[:4]							):
    if ca == ca:
      prefix_len += 1
    else:
      break

  return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(jaro_winkler('hello', 'world'))




'''simple docstring'''






from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream

class 				a__(   lowerCamelCase__      ):







    def __init__( self					:    int		,     __snake_case					:    Callable		,     __snake_case					:    Optional[Features] = None		,     __snake_case					:    str = None		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    Optional[dict] = None		,     __snake_case					:    Optional[int] = None		,     **__snake_case					:    Optional[int]		,     ):
      super().__init__(
          features=__snake_case		,     cache_dir=__snake_case		,     keep_in_memory=__snake_case		,     streaming=__snake_case		,     num_proc=__snake_case		,     **__snake_case		,     )
      a		:   List[Any]	  =	Generator(
          cache_dir=__snake_case		,     features=__snake_case		,     generator=__snake_case		,     gen_kwargs=__snake_case		,     **__snake_case		,     )







    def      lowercase_			( self					:    Any      ):
      # Build iterable dataset
      if self.streaming:
        a		:   Optional[int]	  =	self.builder.as_streaming_dataset(split='train'      )
      # Build regular (map-style) dataset
      else:
        a		:   List[Any]	  =	None
        a		:   Any	  =	None
        a		:   Optional[int]	  =	None
        a		:   List[str]	  =	None

        self.builder.download_and_prepare(
            download_config=__snake_case		,     download_mode=__snake_case		,     verification_mode=__snake_case		,     base_path=__snake_case		,     num_proc=self.num_proc		,     )
        a		:   Dict	  =	self.builder.as_dataset(
            split='train'		,     verification_mode=__snake_case		,     in_memory=self.keep_in_memory      )
      return dataset